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StackStorm vs Terraform: What are the differences?
Introduction
In this article, we will explore the key differences between StackStorm and Terraform.
Scalability: StackStorm is a powerful event-driven automation platform that focuses on automating workflows and tasks across different systems and domains. It provides advanced features like sensor framework, rules engine, and integration packs, which enable seamless scaling and extensibility. On the other hand, Terraform is an infrastructure-as-code (IAC) tool that is primarily designed for managing and provisioning infrastructure resources. It excels in managing cloud resources, offering scalability and reliability in deploying and managing large-scale infrastructure projects.
Focus: StackStorm primarily focuses on automation, event-driven workflows, and integrations. It excels in automating repetitive tasks, orchestrating complex workflows, and integrating various systems. It provides a powerful rule engine, allowing users to trigger actions based on predefined rules and events. In contrast, Terraform focuses on managing infrastructure resources. It allows users to define infrastructure resources in a declarative configuration language and provides a consistent way to deploy and manage those resources across multiple cloud providers or on-premises infrastructure.
Workflow Automation vs. Infrastructure Provisioning: StackStorm is more suited for workflow automation and task management, where it excels in event-driven automation and integrating various systems. It provides a wide range of integrations with popular tools and platforms, making it a flexible and powerful automation solution. Terraform, on the other hand, is designed for provisioning and managing infrastructure resources. It focuses on infrastructure-as-code and provides a unified interface to define and manage infrastructure resources across multiple cloud providers or on-premises infrastructure.
Community and Ecosystem: StackStorm has an active and growing community, with a wide range of pre-built integrations and automation packs available. It provides an open-source platform with a strong focus on community contributions. Terraform also has a vibrant community and a rich ecosystem of providers, allowing users to manage resources across different cloud providers. It benefits from being part of HashiCorp's suite of tools, which includes popular products like Vault and Consul.
Ease of Use and Learning Curve: StackStorm offers a user-friendly and intuitive web-based interface, making it easy to create and manage workflows and automate tasks. It provides a robust set of documentation, guides, and examples, enabling users to quickly get up to speed with the platform. On the other hand, Terraform has a slightly steeper learning curve, especially for users new to infrastructure-as-code. It requires understanding the declarative configuration language and the concepts of resource provisioning and management.
Extensibility and Integration: StackStorm provides a comprehensive framework for integrating with different systems and platforms. It offers a wide range of integration packs that allow users to connect and interact with popular tools and services. Users can easily extend StackStorm's functionality by creating custom integrations or leveraging the existing ones. Terraform also supports integrations, but its primary focus is on managing infrastructure resources rather than deep integration with other systems.
Summary
In summary, StackStorm is a powerful automation platform that excels in event-driven workflows, task management, and system integrations, while Terraform is an infrastructure-as-code tool specifically designed for provisioning and managing infrastructure resources across different cloud providers or on-premises infrastructure. Both tools have their strengths and are suited for different use cases.
Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.
We use Terraform to manage AWS cloud environment for the project. It is pretty complex, largely static, security-focused, and constantly evolving.
Terraform provides descriptive (declarative) way of defining the target configuration, where it can work out the dependencies between configuration elements and apply differences without re-provisioning the entire cloud stack.
AdvantagesTerraform is vendor-neutral in a way that it is using a common configuration language (HCL) with plugins (providers) for multiple cloud and service providers.
Terraform keeps track of the previous state of the deployment and applies incremental changes, resulting in faster deployment times.
Terraform allows us to share reusable modules between projects. We have built an impressive library of modules internally, which makes it very easy to assemble a new project from pre-fabricated building blocks.
DisadvantagesSoftware is imperfect, and Terraform is no exception. Occasionally we hit annoying bugs that we have to work around. The interaction with any underlying APIs is encapsulated inside 3rd party Terraform providers, and any bug fixes or new features require a provider release. Some providers have very poor coverage of the underlying APIs.
Terraform is not great for managing highly dynamic parts of cloud environments. That part is better delegated to other tools or scripts.
Terraform state may go out of sync with the target environment or with the source configuration, which often results in painful reconciliation.
I personally am not a huge fan of vendor lock in for multiple reasons:
- I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
- I've seen S3 failures nearly take down half the internet.
- I've seen companies get stuck in the cloud because they aren't built cloud agnostic.
I choose to use terraform for my cloud provisioning for these reasons:
- It's cloud agnostic so I can use it no matter where I am.
- It isn't difficult to use and uses a relatively easy to read language.
- It tests infrastructure before running it, and enables me to see and keep changes up to date.
- It runs from the same CLI I do most of my CM work from.
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached
Pros of StackStorm
- Auto-remediation7
- Integrations5
- Automation4
- Complex workflows4
- Open source3
- Beautiful UI2
- ChatOps2
- Python2
- Extensibility1
- Slack1
Pros of Terraform
- Infrastructure as code121
- Declarative syntax73
- Planning45
- Simple28
- Parallelism24
- Well-documented8
- Cloud agnostic8
- It's like coding your infrastructure in simple English6
- Immutable infrastructure6
- Platform agnostic5
- Extendable4
- Automation4
- Automates infrastructure deployments4
- Portability4
- Lightweight2
- Scales to hundreds of hosts2
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Cons of StackStorm
- Complexity3
- There are not enough sources of information1
Cons of Terraform
- Doesn't have full support to GKE1
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